更新日期:GMT+8 2025年10月4日 19:40
- 本專案僅限於教育研究用途。
- 請勿將本腳本作為 抄答案、侵權或其他惡意用途。
- 使用者需自行承擔所有風險與後果。
- 作者不對任何因使用本專案所造成的損害負責。
此專案原本是為了研究台灣主要課本/習作出版社的電子書驗證機制,探討其前端身份驗證設計。
| # AFF | |
| # 如果你想支持我,可以通过我的邀请链接购买机场 | |
| # 感谢支持 | |
| # 1. ssLinks 邀请码: fSo2OhzH https://98a6251b6cd7471da86cca993b6dbe6f.36d.biz/#/register?code=fSo2OhzH | |
| # 2. 一元机场 邀请码: r3f1duds https://xn--4gq62f52gdss.top/#/register?code=r3f1duds | |
| # 一定要填我的邀请码,不填我哭给你看😭 | |
| # mihomo (Clash Meta) 懒人配置 | |
| # 版本 V1.23-251221 |
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| """ | |
| The most atomic way to train and run inference for a GPT in pure, dependency-free Python. | |
| This file is the complete algorithm. | |
| Everything else is just efficiency. | |
| @karpathy | |
| """ | |
| import os # os.path.exists | |
| import math # math.log, math.exp |
| name | apple-container |
|---|---|
| description | Apple Silicon Mac で動く軽量 Linux コンテナランタイム `container` の利用者向けリファレンス。`container run`、`container build`、`container image pull/push`、`container machine`、ボリューム・ネットワーク・DNS・設定ファイルなど、日常的なコマンドの使い方を網羅する。`container` コマンドの使い方やトラブルシューティングに関する質問で使用する。 |
Apple 製の container ツールは、Linux コンテナを 軽量 VM 1 つ = コンテナ 1 個 の方式で Mac 上に起動するランタイム。OCI 互換イメージを使うため Docker / podman で作ったイメージがそのまま動く。リポジトリは apple/container。
このスキルは 利用者向け。ソースコードの修正やビルド方法ではなく、
containerコマンドを使う側の知識を扱う。
| "workbench.colorCustomizations": { | |
| // Contrast Colors - The contrast colors are typically only set for high contrast themes. If set, they add an additional border around items across the UI to increase the contrast. | |
| "contrastActiveBorder": "", | |
| "contrastBorder": "", | |
| // Base Colors | |
| "focusBorder": "", | |
| "foreground": "", | |
| "widget.shadow": "", | |
| "selection.background": "", | |
| "descriptionForeground": "", |